The cost of data center server power consumption and the cooling systems to dissipate the generated heat are major expenses in modern data centers where thousands of servers are densely packed in relatively small racks. To maintain effective operation and sustain profitability, it becomes necessary to have power management systems to optimize the power usage with respect to customer requirements. In other words, these power management systems must be able to use minimum power possible and yet be able to satisfy all customer requirements. It is well established that a typical server consumes a relatively high amount of power even it is idle, due to chip leakage current and other supporting components such as disk drives and network routers. Turning a system off and directing all traffic to a subset of available servers during non-peak hours is a common approach to saving power during periods of low traffic. Current technologies for server shutdown are mainly based on manual actions by system administrators or on automated actions driven by simple policies. Based on their experiences and workload history, the system operators may shut down systems for an extended period of time. In doing so, these system operators must anticipate the possibility of sudden increases in traffic, and often they drastically overprovision to ensure adequate performance (and hence customer satisfaction) even under worst case situations. The amount of manual effort by system administrators is costly, and so is the over provisioning that is typically done to ensure that performance goals are met—particularly as energy costs continue to mount.
New power management strategies that turn servers on and off in real time as workload fluctuates have been investigated. While turning a server off can save energy costs, and perhaps licensing fees as well, a countervailing factor that must be considered is the cost of turning a server on or off. There are several components to this cost. First, during the time that a server is being powered down or up, it is still consuming energy but is not doing any useful work. Second, every time a server is power-cycled, the thermal changes induce more wear and tear on the server, and thus frequent cycling may shorten the lifetime of the server, leading to an increased failure rate and a concomitant increase in replacement cost. Third, 1 to 5 minutes may elapse when restoring a server from shut-down state to a state in which it is fully available for use, depending on system applications and configurations. This may not be fast enough to react to a sudden increase in traffic, resulting in Service Level Agreements (SLA) violations, which may be subject to monetary penalties. All of these problematic costs reduce the usefulness of the strategy of turning servers on and off dynamically, preventing power management strategies of this nature from being deployed widely.
It is therefore desirable to place these unneeded devices into intermediate states of “readiness” such as “standby” or “hibernate” from which the devices may be activated more quickly. These states consume more power than when the device is powered down, and generally have longer activation times than the idle state. Moreover, as common in data center environments with distributed resources, the overall infrastructure is generally composed of different physical components with different power-performance characteristics, different power management capabilities and different power-state-transition latencies. Therefore, the overall system efficiency can vary dramatically by the order which the hosts are chosen to transition into different power states.
At present, there are no algorithms known in the art for managing these tradeoffs between the desire to conserve energy and the desire to be responsive to surges in workload behavior.